A forensics method of web browsing behavior based on association rule mining

Author

Yiyun Zhang ; Guolong Chen

Author_Institution

Coll. of Math. & Comput. Sci., Univ. Fuzhou, Fuzhou, China

fYear

2014

fDate

15-17 Nov. 2014

Firstpage

927

Lastpage

932

Abstract

With the development of network, web forensics is becoming more and more important due to the rampant cybercrime. In this paper, a forensics method of web browsing behavior based on association rule mining is presented. The method aims at providing the necessary data support to build the behavior pattern library for investigation. The records of the user´s browsing history are collected to be analyzed. The obtained original data are pretreated to transactional data which are suitable for association rule mining. Frequent browsing time and frequent web browsing sequences are obtained from the transactional data by Apriori algorithm. The mining results are helpful for identification and recognition of anonymous or suspicious web browsing behavior patterns.

Keywords

Internet; computer crime; data mining; digital forensics; Apriori algorithm; anonymous Web browsing behavior patterns; association rule mining; behavior pattern library; record analysis; record collection; suspicious Web browsing behavior patterns; transactional data; user browsing history; Association rules; Browsers; Forensics; History; Libraries; Uniform resource locators; apriori algorithm; association rule minings; browsing behavior patterns; firefox; forensics investigation; frequent itemset; web log mining;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems and Informatics (ICSAI), 2014 2nd International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4799-5457-5

Type

conf

DOI

10.1109/ICSAI.2014.7009418

Filename

7009418